The Experts below are selected from a list of 15 Experts worldwide ranked by ideXlab platform
Klausjurgen Bathe - One of the best experts on this subject based on the ideXlab platform.
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the bathe time integration Method revisited for prescribing desired numerical dissipation
Computers & Structures, 2019Co-Authors: Mohammad Mahdi Malakiyeh, S Shojaee, Klausjurgen BatheAbstract:Abstract In this paper we further consider the Bathe Method for the direct time integration in structural dynamics and wave propagations. The Method uses two sub-steps per time step and is an unconditionally stable scheme frequently used without adjusting any parameter. In the first sub-step the trapezoidal rule is used and in the second sub-step the 3-point Euler Backward Method is employed. In this contribution we derive the Method using, instead of the Euler scheme, the 3-point trapezoidal rule for the complete step with two Newmark parameters. The parameters can then be used to smoothly prescribe desired numerical dissipation, from zero to very significant dissipation. To highlight the performance of the Method, the stability, accuracy and overshooting are studied and some illustrative problems are solved. The results are compared with those of some other Methods that also use parameters to introduce numerical dissipation. We conclude that the use of the parameters in the Bathe Method can be valuable but probably will require some numerical experimentation.
R Kreisig - One of the best experts on this subject based on the ideXlab platform.
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finite strain viscoplasticity with nonlinear kinematic hardening phenomenological modeling and time integration
Computer Methods in Applied Mechanics and Engineering, 2008Co-Authors: A. V. Shutov, R KreisigAbstract:Abstract This article deals with a viscoplastic material model of overstress type. The model is based on a multiplicative decomposition of the deformation gradient into elastic and inelastic part. An additional multiplicative decomposition of inelastic part is used to describe a nonlinear kinematic hardening of Armstrong–Frederick type. Two implicit time-stepping Methods are adopted for numerical integration of evolution equations, such that the plastic incompressibility constraint is exactly satisfied. The first Method is based on the tensor exponential. The second Method is a modified Euler-Backward Method. Special numerical tests show that both approaches yield similar results even for finite inelastic increments. The basic features of the material response, predicted by the material model, are illustrated with a series of numerical simulations.
Mohammad Mahdi Malakiyeh - One of the best experts on this subject based on the ideXlab platform.
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the bathe time integration Method revisited for prescribing desired numerical dissipation
Computers & Structures, 2019Co-Authors: Mohammad Mahdi Malakiyeh, S Shojaee, Klausjurgen BatheAbstract:Abstract In this paper we further consider the Bathe Method for the direct time integration in structural dynamics and wave propagations. The Method uses two sub-steps per time step and is an unconditionally stable scheme frequently used without adjusting any parameter. In the first sub-step the trapezoidal rule is used and in the second sub-step the 3-point Euler Backward Method is employed. In this contribution we derive the Method using, instead of the Euler scheme, the 3-point trapezoidal rule for the complete step with two Newmark parameters. The parameters can then be used to smoothly prescribe desired numerical dissipation, from zero to very significant dissipation. To highlight the performance of the Method, the stability, accuracy and overshooting are studied and some illustrative problems are solved. The results are compared with those of some other Methods that also use parameters to introduce numerical dissipation. We conclude that the use of the parameters in the Bathe Method can be valuable but probably will require some numerical experimentation.
Eric W Weisstein - One of the best experts on this subject based on the ideXlab platform.
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Euler Backward Method
2002Co-Authors: Eric W WeissteinAbstract:An implicit Method for solving an ordinary differential equation that uses f(x_n,y_n) in y_(n+1). In the case of a heat equation, for example, this means that a linear system must be solved at each time step. However, unlike the Euler forward Method, the Backward Method is unconditionally stable and so allows large time steps to be taken.
Ondrej Holub - One of the best experts on this subject based on the ideXlab platform.
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dual estimation constructing building energy models from data sampled at low rate
Applied Energy, 2016Co-Authors: Simone Aldi, Shuai Yua, Pe Endel, Ondrej HolubAbstract:Estimation of energy models from data is an important part of advanced fault detection and diagnosis tools for smart energy purposes. Estimated energy models can be used for a large variety of management and control tasks, spanning from model predictive building control to estimation of energy consumption and user behavior. In practical implementation, problems to be considered are the fact that some measurements of relevance are missing and must be estimated, and the fact that other measurements, collected at low sampling rate to save memory, make discretization of physics-based models critical. These problems make classical estimation tools inadequate and call for appropriate dual estimation schemes where states and parameters of a system are estimated simultaneously. In this work we develop dual estimation schemes based on Extended Kalman Filtering (EKF) and Unscented Kalman Filtering (UKF) for constructing building energy models from data: in order to cope with the low sampling rate of data (with sampling time 15min), an implicit discretization (Euler Backward Method) is adopted to discretize the continuous-time heat transfer dynamics. It is shown that explicit discretization Methods like the Euler forward Method, combined with 15min sampling time, are ineffective for building reliable energy models (the discrete-time dynamics do not match the continuous-time ones): even explicit Methods of higher order like the Runge–Kutta Method fail to provide a good approximation of the continuous-time dynamics which such large sampling time. Either smaller time steps or alternative discretization Methods are required. We verify that the implicit Euler Backward Method provides good approximation of the continuous-time dynamics and can be easily implemented for our dual estimation purposes. The applicability of the proposed Method in terms of estimation of both states and parameters is demonstrated via simulations and using historical data from a real-life building.